Software Engineer, Compute Infrastructure

Details

About Glean:

Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With 100+ enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean provides infrastructure to govern, scale, and customize AI across the business.

About the Role:

Glean is seeking a Software Engineer, Compute Infrastructure to design, build, and operate the core compute and runtime platform that powers AI search, assistant, and agentic workloads. This role sits within Platforms and focuses on Kubernetes-based runtime systems, multi-cloud infrastructure, and cost-efficient, low-latency execution for production services and pipelines serving customers at scale.

Responsibilities

• Design, build, and own backend/platform services that power Glean’s runtime infrastructure with a focus on reliability, scalability, and performance for AI and search workloads.
• Develop and evolve Kubernetes-based runtime primitives (service orchestration, scheduling integrations, autoscaling patterns) across a multi-cloud foundation (GCP, AWS, Azure).
• Collaborate with platform, data, and product engineering teams to simplify spinning up new services and batch workloads with clear golden paths for deployment, configuration, and runtime operations.
• Drive end-to-end improvements in latency, resource utilization, and cost for core platform services, including multitenant runtime environments and experimental AI workloads.
• Implement and harden infrastructure-as-code patterns, observability, and guardrails so teams can confidently ship and run services in production (SLOs, dashboards, alerts, safe rollout/rollback).
• Partner with Costs and Runtime teams to build shared mechanisms for attribution, guardrails, and automation that keep the runtime layer efficient as customers and traffic grow.
• Participate in an on-call rotation for critical platform services, lead incident response when needed, and translate learnings into improved reliability, tooling, and documentation.
• Contribute to technical direction for Runtime Infra: define roadmaps around multitenancy, autoscaling, capacity/placement, and platformized patterns that reduce per-team hand-holding.

Requirements (About you)

• Backend/platform engineer comfortable working where application behavior, infrastructure, and cost intersect, and motivated by building shared systems used by many teams.
• Strong distributed systems fundamentals and experience operating high-throughput, low-latency services or batch pipelines in production.
• Comfortable owning systems end-to-end: design, implementation, testing, deployment, observability, and ongoing operations.
• Familiar with reliability and guardrails: SLOs, incident response, safe deployment strategies, and operational runbooks.
• Pragmatic and execution-oriented: able to balance ideal architectures with startup constraints and ship iterative improvements.
• Clear communicator who collaborates across infra and product engineering to translate requirements into platform capabilities.
• Excited to work in a multi-cloud, multi-tenant environment and help define best practices for running AI workloads efficiently at scale.

Location and Office Policy

• Hybrid: 4 days a week in the Mountain View office (Mountain View, CA, United States).

Compensation & Benefits

• Standard base salary range: $140,000 - $220,000 annually. Compensation will be determined by factors such as location, level, knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.
• Benefits include Medical, Vision, Dental, generous time-off policy, 401(k) contributions, home office improvement stipend, annual education and wellness stipends, company events, and daily lunches.

AI-First Mindset at Glean

AI fluency is core to how Glean works. As part of the interview process, candidates complete a brief AI-focused exercise or discussion to demonstrate how they design and use AI to drive impact in their role.

Global Data Privacy Notice for Job Candidates and Applicants

Depending on location, GDPR, CCPA, or other privacy laws may regulate how applicant data is managed. The full notice is available in Glean’s Privacy Policy. US applicants are subject to arbitration of disputes per the Applicant Arbitration Agreement.